Image decoder

ABSTRACT

An image decoder includes a demultiplexer which extracts motion vector information and quantized DCT coefficients from input information to be decoded, a dequantizer which dequantizes the quantized DCT coefficients to obtain DCT coefficients, an inverse DCT converter which performs inverse DCT conversion on the DCT coefficients to obtain an error image, a prediction image synthesizer which synthesizes a prediction image by performing motion compensation using the motion vector information and a reference image which is a previously decoded image, and an adder which adds the prediction image to the error image to obtain a decoded image. The motion compensation is performable using a positive rounding method and a negative rounding method for interpolating intensity values of pixels in performing the motion compensation.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of application Ser. No. 09/093,194filed on Jun. 8, 1998, now U.S. Pat. No. 6,295,376, the contents ofwhich are hereby incorporated herein by reference in their entirety.

This application is related to application Ser. No. 09/513,688 filed onFeb. 25, 2000; application Ser. No. 09/514,287 filed on Feb. 28, 2000;application Ser. No. 09/516,207 filed on Feb. 29, 2000; application Ser.No. 09/516,245 filed on Mar. 1, 2000; application Ser. No. 09/875,928filed on Jun. 8, 2001; application Ser. No. 09/875,929 filed on Jun. 8,2001; application Ser. No. 09/875,930 filed on Jun. 8, 2001; andapplication Ser. No. 09/875,932 filed on Jun. 8, 2001, all of which,like the present application, are continuations of application Ser. No.09/093,194 filed on Jun. 8, 1998.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to an image sequence coding and decodingmethod which performs interframe prediction using quantized values forchrominance or luminance intensity.

2. Description of Related Art

In high efficiency coding of image sequences, interframe prediction(motion compensation) by utilizing the similarity of adjacent framesover time, is known to be a highly effective technique for datacompression. Today's most frequently used motion compensation method isblock matching with half pixel accuracy, which is used in internationalstandards H.263, MPEG1, and MPEG2. In this method, the image to be codedis segmented into blocks and the horizontal and vertical components ofthe motion vectors of these blocks are estimated as integral multiplesof half the distance between adjacent pixels. This process is describedusing the following equation:

[Equation 1]

P(x,y)=R(x+u _(i) ,y+v _(i)(x,y) εB _(i),0≦i<N  (1)

where P(x, y) and R(x, y) denote the sample values (luminance orchrominance intensity) of pixels located at coordinates (x, y) in thepredicted image P of the current frame and the reference image (decodedimage of a frame which has been encoded before the current frame) R,respectively. x and y are integers, and it is assumed that all thepixels are located at points where the coordinate values are integers.Additionally it is assumed that the sample values of the pixels arequantized to non-negative integers. N, Bi, and (ui, vi) denote thenumber of blocks in the image, the set of pixels included in the i-thblock of the image, and the motion vectors of the i-th block,respectively.

When the values for ui and vi are not integers, it is necessary to findthe intensity value at the point where no pixels actually exist in thereference image. Currently, bilinear interpolation using the adjacentfour pixels is the most frequently used method for this process. Thisinterpolation method is described using the following equation:$\begin{matrix}\text{[Equation 2]} & \quad \\\begin{matrix}{R\left( {{x + \frac{p}{d}},{{y + \frac{q}{d}} = \quad \left( {{\left( {d - q} \right)\quad \left( {{\left( {d - p} \right){R\left( {x,y} \right)}} + {{pR}\left( {{x + 1},y} \right)}} \right)} +} \right.}} \right.} \\{\left. \quad {q\left( {{\left( {d - p} \right){R\left( {x,{y + 1}} \right)}} + {{pR}\left( {{x + 1},{y + 1}} \right)}} \right)} \right)//d^{2}}\end{matrix} & (2)\end{matrix}$

where d is a positive integer, and p and q are smaller than d but notsmaller than 0. “//” denotes integer division which rounds the result ofnormal division (division using real numbers) to the nearest integer.

An example of the structure of an H.263 video encoder is shown in FIG.1. As the coding algorithm, H.263 adopts a hybrid coding method(adaptive interframe/intraframe coding method) which is a combination ofblock matching and DCT (discrete cosine transform). A subtractor 102calculates the difference between the input image (current frame baseimage) 101 and the output image 113 (related later) of theinterframe/intraframe coding selector 119, and then outputs an errorimage 103. This error image is quantized in a quantizer 105 after beingconverted into DCT coefficients in a DCT converter 104 and then formsquantized DCT coefficients 106. These quantized DCT coefficients aretransmitted through the communication channel while at the same timeused to synthesize the interframe predicted image in the encoder. Theprocedure for synthesizing the predicted image is explained next. Theabove mentioned quantized DCT coefficients 106 forms the reconstructederror image 110 (same as the reconstructed error image on the receiveside) after passing through a dequantizer 108 and inverse DCT converter109. This reconstructed error image and the output image 113 of theinterframe/intraframe coding selector 119 is added at the adder 111 andthe decoded image 112 of the current frame (same image as the decodedimage of current frame reconstructed on the receiver side) is obtained.This image is stored in a frame memory 114 and delayed for a time equalto the frame interval. Accordingly, at the current point, the framememory 114 outputs the decoded image 115 of the previous frame. Thisdecoded image of the previous frame and the original image 101 of thecurrent frame are input to the block matching section 116 and blockmatching is performed between these images. In the block matchingprocess, the original image of the current frame is segmented intomultiple blocks, and the predicted image 117 of the current frame issynthesized by extracting the section most resembling these blocks fromthe decoded image of the previous frame. In this process, it isnecessary to estimate the motion between the prior frame and the currentframe for each block. The motion vector for each block estimated in themotion estimation process is transmitted to the receiver side as motionvector data 120. On the receiver side, the same prediction image as onthe transmitter side is synthesized using the motion vector informationand the decoding image of the previous frame. The prediction image 117is input along with a “0” signal 118 to the interframe/intraframe codingselector 119. This switch 119 selects interframe coding or intraframecoding by selecting either of these inputs. Interframe coding isperformed when the prediction image 117 is selected (this case is shownin FIG. 2). On the other hand when the “0” signal is selected,intraframe coding is performed since the input image itself isconverted, to a DCT coefficients and output to the communicationchannel. In order for the receiver side to correctly reconstruct thecoded image, the reciever must be informed whether intraframe coding orinterframe coding was performed on the transmitter side. Consequently,an identifier flag 121 is output to the communication circuit. Finally,an H.263 coded bitstream 123 is acquired by multiplexing the quantizedDCT coefficients, motion vectors, the and interframe/intraframeidentifier flag information in a multiplexer 122.

The structure of a decoder 200 for receiving the coded bit stream outputfrom the encoder of FIG. 1 is shown in FIG. 2. The H.263 coded bitstream 217 that is received is demultiplexed into quantized DCTcoefficients 201, motion vector data 202, and a interframe/intraframeidentifier flag 203 in the demultiplexer 216. The quantized DCTcoefficients 201 become a decoded error image 206 after being processedby an inverse quantizer 204 and inverse DCT converter 205. This decodederror image is added to the output image 215 of theinterframe/intraframe coding selector 214 in an adder 207 and the sum ofthese images is output as the decoded image 208. The output of theinterframe/intraframe coding selector is switched according to theinterframe/intraframe identifier flag 203. A prediction image 212utilized when performing interframe encoding is synthesized in theprediction image synthesizer 211. In this synthesizer, the position ofthe blocks in the decoded image 210 of the prior frame stored in framememory 209 is shifted according to the motion vector data 202. On theother hand, for intraframe coding, the interframe /intraframe codingselector outputs the “0” signal 213 as is.

SUMMARY OF THE INVENTION

The image encoded by H.263 is comprised of a luminance plane (Y plane)containing luminance information, and two chrominance planes (U planeand V plane) containing chrominance information. At this time,characteristically, when the image has 2m pixels in the horizontaldirection and 2n pixels in the vertical direction (m and n are positiveintegers), the Y plane has 2m pixels horizontally and 2n pixelsvertically, the U and V planes have m pixels horizontally and n pixelsvertically. The low resolution on the chrominance plane is due to thefact that the human visual system has a comparatively dull visualfaculty with respect to spatial variations in chrominance. Having suchimage as an input, H. 263 performs coding and decoding in block unitsreferred to as macroblocks. The structure of a macroblock is shown inFIG. 3. The macroblock is comprised of three blocks; a Y block, U blockand V block. The size of the Y block 301 containing the luminanceinformation is 16×16 pixels, and the size of the U block 302 and V block303 containing the chrominance information is 8×8 pixels.

In H. 263, half pixel accuracy block matching is applied to each block.Accordingly, when the estimated motion vector is defined as (u, v), uand v are both integral multiples of half the distance between pixels.In other words, ½ is used as the minimum unit. The configuration of theinterpolation method used for the intensity values (hereafter theintensity values for “luminance” and “chrominance” are called by thegeneral term “intensity value”) is shown in FIG. 4. When performing theinterpolation described in equation 2, the quotients of division arerounded off to the nearest integer, and further, when the quotient has ahalf integer value (i.e. 0.5 added to an integer), rounding off isperformed to the next integer in the direction away from zero. In otherwords, in FIG. 4, when the intensity values for 401, 402, 403, 404 arerespectively La, Lb, Lc, and Ld (La, Lb, Lc, and Ld are non-negativeintegers), the interpolated intensity values Ia, Ib, Ic, and Id (Ia, Ib,Ic, and Id are non-negative integers) at positions 405, 406, 407, 408are expressed by the following equation: $\begin{matrix}\text{[Equation 3]} & \quad \\{{{Ia} = {La}}{{Ib} = \left\lbrack {\left( {{La} + {Lb} + 1} \right)/2} \right\rbrack}{{Ic} = \left\lbrack {\left( {{La} + {Lc} + 1} \right)/2} \right\rbrack}{{Id} = \left\lbrack {\left( {{La} + {Lb} + {Lc} + {Ld} + 2} \right)/4} \right\rbrack}} & (3)\end{matrix}$

where “[ ]” denotes truncation to the nearest integer towards 0 (i.e.the fractional part is discarded). The expectation of the errors causedby this rounding to integers is estimated as follows: It is assumed thatthe probability that the intensity value at positions 405, 406, 407, and408 of FIG. 4 is used is all 25 percent. When finding the intensityvalue Ia for position 405, the rounding error will clearly be zero.Also, when finding the intensity value Ib for position 406, the errorwill be zero when La+Lb is an even number, and when an odd number theerror is ½. If the probability that La+Lb will be an even number and anodd number is both 50 percent, then the expectation for the error willbe 0×½+½×½=¼. Further, when finding the intensity value Ic for position407, the expectation for the error is ¼ as for Ib. When finding theintensity value Id for position 408, the error when the residual ofLa+Lb+Lc+Ld divided by four are 0, 1, 2, and 3 are respectively 0, −¼,½, and ¼. If we assume that the probability that the residual is 0, 1,2, and 3 is all equal (i.e. 25 percent), the expectation for the erroris 0×¼−¼×¼+½×¼+¼×¼=⅛. As described above, assuming that the possibilitythat the intensity value at positions 405-408 being used are all equal,the final expectation for the error is 0×¼+¼×¼+¼×¼+⅛×¼={fraction(5/32)}. This indicates that each time motion compensation is performedby means of block matching, an error of {fraction (5/32)} occurs in thepixel intensity value. Generally in low rate coding, sufficient numberof bits cannot be used for the encoding of the interframe errordifference so that the quantized step size of the DCT coefficient isprone to be large. Accordingly, errors occurring due to motioncompensation are corrected only when it is very large. When interframeencoding is performed continuously without performing intraframe codingunder such environment, the errors tend. to accumulate and cause badeffects on the reconstructed image.

Just as explained above, the number of pixels is about half in both thevertical and horizontal direction on the chrominance plane. Therefore,for the motion vectors of the U block and V block, half the value of themotion vector for the Y block is used for the vertical and horizontalcomponents. Since the horizontal and vertical components of the motionvector for the Y block motion vector are integral multiples of ½, themotion vector components for the U and V blocks will appear as integralmultiples of ¼ (quarter pixel accuracy) if ordinary division isimplemented. However, due to the high computational complexity of theintensity interpolation process for motion vectors with quarter pixelaccuracy, the motion vectors for U and V blocks are rounded to halfpixel accuracy in H.263. The rounding method utilized in H.263 is asfollows: According to the definition described above, (u, v) denotes themotion vector of the macroblock (which is equal to the motion vector forthe Y block). Assuming that r is an integer and s is an non-negativeinteger smaller than 4, u/2 can be rewritten as u/2=r+s/4. When s is 0or 2, no rounding is required since u/2 is already an integral multipleof ½. However when s is equal to 1 or 3, the value of s is rounded to 2.By increasing the possibility that s takes the value of 2 using thisrounding method, the filtering effect of motion compensation can beemphasized. When the probability that the value of s prior to roundingis 0, 1, 2, and 3 are all 25 percent, the probability that s will be 0or 2 after rounding will respectively be 25 percent and 75 percent. Theabove explained process related to the horizontal component u of themotion vector is also applied to the vertical component v. Accordingly,in the U block and V block, the probability for using the intensityvalue of the 401 position is ¼×¼={fraction (1/16)}, and the probabilityfor using the intensity value of the 402 and 403 positions is both¼×¾={fraction (3/16)}, while the probability for using the intensityvalue of position 404 is ¾×¾={fraction (9/16)}. By utilizing the samemethod as above, the expectation for the error of the intensity value is0×{fraction (1/16)}+¼×{fraction (3/16)}+¼×{fraction (3/16)}+⅛×{fraction(9/16)}={fraction (21/128)}. Just as explained above for the Y block,when interframe encoding is continuously performed, the problem ofaccumulated errors occurs.

As related above, for image sequence coding and decoding methods inwhich interframe prediction is performed and luminance or chrominanceintensity is quantized, the problem of accumulated rounding errorsoccurs. This rounding error is generated when the luminance orchrominance intensity value is quantized during the generation of theinterframe prediction image.

In view of the above problems, it is therefore an object of thisinvention, to improve the quality of the reconstructed image bypreventing error accumulation.

In order to achieve the above object, the accumulation of errors isprevented by limiting the occurrence of errors or performing anoperation to cancel out errors that have occurred.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing the layout of the H.263 image encoder.

FIG. 2 is a block diagram showing the layout of the H.263 image decoder.

FIG. 3 is a drawing showing the structure of the macro block.

FIG. 4 is a drawing showing the interpolation process of intensityvalues for block matching with half pixel accuracy.

FIG. 5 is a drawing showing a coded image sequence.

FIG. 6 is a block diagram showing a software image encoding device.

FIG. 7 is a block diagram showing a software image decoding device.

FIG. 8 is a flow chart showing an example of processing in the softwareimage encoding device.

FIG. 9 is a flow chart showing an example of the coding mode decisionprocessing for the software image encoding device.

FIG. 10 is a flow chart showing an example of motion estimation andmotion compensation processing in the software image encoding device.

FIG. 11 is a flow chart showing the processing in the software imagedecoding device.

FIG. 12 is a flow chart showing an example of motion compensationprocessing in the software image decoding device.

FIG. 13 is a drawing showing an example of a storage media on which anencoded bit stream generated by an encoding method that outputs bitstreams including I, P+ and P− frames is recorded.

FIG. 14 is a set of drawings showing specific examples of devices usingan encoding method where P+ and P− frames coexist.

FIG. 15 is a drawing showing an example of a storage media on which anencoded bit stream generated by an encoding method the outputs bitstreams including I, B, P+, and P− frames is recorded.

FIG. 16 is a block diagram showing an example of a block matching unitincluded in a device using an encoding method where P+ and P− framescoexist.

FIG. 17 is a block diagram showing the prediction image synthesizerincluded in a device for decoding bit streams encoded by an encodingmethod where P+ and P− frames coexist.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

First, in which circumstances the accumulated rounding errors as relatedin the “Prior art” occur must be considered. An example of an imagesequences encoded by coding methods which can perform bothunidirectional prediction and bidirectional prediction such as inMPEG.1, MPEG.2 and H.263 is shown in FIG. 5. An image 501 is a framecoded by means of intraframe coding and is referred to as an I frame. Incontrast, images 503, 505, 507, 509 are called P frames and are coded byunidirectional interframe coding by using the previous I or P frame asthe reference image. Accordingly, when for instance encoding image 505,image 503 is used as the reference image and interframe prediction isperformed. Images 502, 504, 506 and 508 are called B frames andbidirectional interframe prediction is performed utilizing the previousand subsequent I or P frame. The B frame is characterized by not beingused as a reference image when interframe prediction is performed. Sincemotion compensation is not performed in I frames, the rounding errorcaused by motion compensation will not occur. In contrast, not only ismotion compensation performed in the P frames but the P frame is alsoused as a reference image by other P or B frames so that it may be acause leading to accumulated rounding errors. In the B frames on theother hand, motion compensation is performed so that the effect ofaccumulated rounding errors appears in the reconstructed image. However,due to the fact that B frames are not used as reference images, B framescannot be a source of accumulated rounding errors. Thus, if accumulatedrounding errors can be prevented in the P frame, then the bad effects ofrounding errors can be alleviated in the overall image sequence. InH.263 a frame for coding a P frame and a B frame exists and is called aPB frame (For instance, frames 503 and 504 can both be encoded as a PBframe.) If the combined two frames are viewed as separate frames, thenthe same principle as above can be applied. In other words, ifcountermeasures are taken versus rounding errors for the P frame partwithin a PB frame, then the accumulation of errors can be prevented.

Rounding errors occur during interpolation of intensity values when avalue obtained from normal division (division whose operation result isa real number) is a half integer (0.5 added to an integer) and thisresult is then rounded up to the next integer in the direction away fromzero. For instance, when dividing by 4 to find an interpolated intensityvalue is performed, the rounding errors for the cases when the residualis 1 and 3 have equal absolute values but different signs. Consequently,the rounding errors caused by these two cases are canceled when theexpectation for the rounding errors is calculated (in more generalwords, when dividing by a positive integer d′ is performed, the roundingerrors caused by the cases when the residual is t and d′−t arecancelled). However, when the residual is 2, in other words when theresult of normal division is a half integer, the rounding error cannotbe canceled and leads to accumulated errors. To solve this problem, amethod that allows the usage of two rounding methods can be used. Thetwo rounding methods used here are: a rounding method that rounds halfintegers away from 0; and a rounding method that rounds half integerstowards 0. By combining the usage of these two rounding methods, therounding errors can be canceled. Hereafter, the rounding method thatrounds the result of normal division to the nearest integer and roundshalf integer values away from 0 is called “positive rounding”.Additionally, the rounding method that rounds the result of normaldivision to the nearest integer and rounds half integer values towards 0is called “negative rounding”. The process of positive rounding used inblock matching with half pixel accuracy is shown in Equation 3. Whennegative rounding is used instead, this equation can be rewritten asshown below. $\begin{matrix}\text{[Equation 4]} & \quad \\{{{Ia} = {La}}{{Ib} = \left\lbrack {\left( {{La} + {Lb}} \right)/2} \right\rbrack}{{Ic} = \left\lbrack {\left( {{La} + {Lc}} \right)/2} \right\rbrack}{{Id} = \left\lbrack {\left( {{La} + {Lb} + {Lc} + {Ld} + 1} \right)/4} \right\rbrack}} & (4)\end{matrix}$

Hereafter motion compensation methods that performs positive andnegative rounding for the synthesis of interframe prediction images arecalled “motion compensation using positive rounding” and “motioncompensation using negative rounding”, respectively. Furthermore, f or Pframes which use block matching with half pixel accuracy for motioncompensation, a frame that uses positive rounding is called a “P+ frame”and a frame that uses negative rounding is called a “P− frame” (underthis definition, the P frames in H.263 are all P+ frames). Theexpectation for the rounding errors in P+ and P− frames have equalabsolute values but different signs. Accordingly, the accumulation ofrounding errors can be prevented when P+ frames and P− frames arealternately located along the time axis. In the example in FIG. 5, ifthe frames 503 and 507 are set as P+ frames and the frames 505 and 509are set as P− frames, then this method can be implemented. The alternateoccurrence of P+ frames and P− frames leads to the usage of a P+ frameand a P− frame in the bidirectional prediction for B frames. Generally,the average of the forward prediction image (i.e. the prediction imagesynthesized by using frame 503 when frame 504 in FIG. 5 is beingencoded) and the backward prediction image (i.e. the prediction imagesynthesized by using frame 505 when frame 504 in FIG. 5 is beingencoded) is frequently used for synthesizing the prediction image for Bframes. This means that using a P+ frame (which has a positive value forthe expectation of the rounding error) and a P− frame (which has anegative value for the expectation of the rounding error) inbidirectional prediction for a B frame is effective in canceling out theeffects of rounding errors. Just as related above, the rounding processin the B frame will not be a cause of error accumulation. Accordingly,no problem will occur even if the same rounding method is applied to allthe B frames. For instance, no serious degradation of decoded images iscaused even if motion compensation using positive rounding is performedfor all of the B frames 502, 504, 506, and 508 in FIG. 5. Preferablyonly one type of rounding is performed for a B frame, in order tosimplify the B frame decoding process.

A block matching section 1600 of an image encoder according to the abovedescribed motion compensation method utilizing multiple rounding methodsis shown in FIG. 16. Numbers identical to those in other drawingsindicate the same part. By substituting the block matching section 116of FIG. 1 with 1600, multiple rounding methods can be used. Motionestimation processing between the input image 101 and the decoded imageof the previous frame is performed in a motion estimator 1601. As aresult, motion information 120 is output. This motion information isutilized in the synthesis of the prediction image in a prediction imagesynthesizer 1603. A rounding method determination device 1602 determineswhether to use positive rounding or negative rounding as the roundingmethod for the frame currently being encoded. Information 1604 relatingto the rounding method that was determined is input to the predictionimage synthesizer 1603. In this prediction image synthesizer 1603, aprediction image 117 is synthesized and output based on the roundingmethod determined by means of information 1604. In the block matchingsection 116 in FIG. 1, there are no items equivalent to 1602, 1604 ofFIG. 16, and the prediction image is synthesized only by positiverounding. Also, the rounding method 1605 determined at the blockmatching section can be output, and this information can then bemultiplexed into the bit stream and be transmitted.

A prediction image synthesizer 1700 of an image decoder which can decodebit streams generated by a coding method using multiple rounding methodsis shown in FIG. 17. Numbers identical to those in other drawingsindicate the same part. By substituting the prediction image synthesizer211 of FIG. 2 by 1700, multiple rounding methods can be used. In therounding method determination device 1701, the rounding methodappropriate for prediction image synthesis in the decoding process isdetermined. In order to carry out decoding correctly, the roundingmethod selected here must be the same as the rounding method that wasselected for encoding. For instance the following rule can be sharedbetween the encoder and decoder: When the current frame is a P frame andthe number of P frames (including the current frame) counted from themost recent I frame is odd, then the current frame is a P+ frame. Whenthis number is even, then the current frame is a P− frame. If therounding method determination device on the encoding side (For instance,1602 in FIG. 16) and the rounding method determination device 1701conform to this common rule, then the images can correctly be decoded.The prediction image is synthesized in the prediction image synthesizer1703 using motion information 202, decoding image 210 of the priorframe, and information 1702 related to the rounding method determined asjust described. This prediction image 212 is output and then used forthe synthesis of the decoded image. As an alternative to the abovementioned case, a case where the information related to the roundingmethod is multiplexed in the transmitted bit stream can also beconsidered (such bit stream can be generated at the encoder byoutputting the information 1605 related to the rounding method from theblock matching section depicted in FIG. 16). In such case, the roundingmethod determiner device 1701 is not used, and information 1704 relatedto the rounding method extracted from the encoded bit stream is used atthe prediction image synthesizer 1703.

Besides the image encoder and the image decoder utilizing the customcircuits and custom chips of the conventional art as shown in FIG. 1 andFIG. 2, this invention can also be applied to software image encodersand software image decoders utilizing general-purpose processors. Asoftware image encoder 600 and a software image decoder 700 are shown inFIG. 6 and FIG. 7. In the software image encoder 600, an input image 601is first stored in the input frame memory 602 and the general-purposeprocessor 603 loads information from here and performs encoding. Theprogram for driving this general-purpose processor is loaded from astorage device 608 which can be a hard disk, floppy disk, etc. andstored in a program memory 604. This general-purpose processor also usesa process memory 605 to perform the encoding. The encoding informationoutput by the general-purpose processor is temporarily stored in theoutput buffer 606 and then output as an encoded bit stream 607.

A flowchart for the encoding software (recording medium readable bycomputer) is shown in FIG. 8. The process starts in 801, and the value 0is assigned to variable N in 802. Next, in 803 and 804, the value 0 isassigned to N when the value for N is 100. N is a counter for the numberof frames. 1 is added for each one frame whose processing is complete,and values from 0 to 99 are allowed when performing coding. When thevalue for N is 0, the current frame is an I frame. When N is an oddnumber, the current frame is a P+ frame, and when an even number otherthan 0, the current frame is a P− frame. When the upper limit for thevalue of N is 99, it means that one I frame is coded after 99 P frames(P+ frames or P− frames) are coded. By always inserting one I frame in acertain number of coded frames, the following benefits can be obtained:(a) Error accumulation due to a mismatch between encoder and decoderprocessing can be prevented (for instance, a mismatch in the computationof DCT); and (b) The processing load for acquiring the reproduced imageof the target frame from the coded data (random access) is reduced. Theoptimal N value varies when the encoder performance or the environmentwhere the encoder is used are changed. It does not mean, therefore, thatthe value of N must always be 100. The process for determining therounding method and coding mode for each frame is performed in 805 andthe flowchart with details of this operation is shown in FIG. 9. Firstof all, whether N is a 0 or not is checked in 901. If N is 0, then ‘I’is output as distinction information of the prediction mode, to theoutput buffer in 902. This means that the image to be coded is will becoded as an I frame. Here, “output to the output buffer” means thatafter being stored in the output buffer, the information is output to anexternal device as a portion of the coded bit stream. When N is not 0,then whether N is an odd or even number is identified in 904. When N isan odd number, ‘+’ is output to the output buffer as the distinctioninformation for the rounding method in 905, and the image to be codedwill be coded as a P+ frame. On the other hand, when N is an evennumber, ‘−’ is output to the output buffer as the distinctioninformation for the rounding method in 906, and the image to be codedwill be coded as a P− frame. The process again returns to FIG. 8, whereafter determining the coding mode in 805, the input image is stored inthe frame memory A in 806. The frame memory A referred to here signifiesa portion of the memory zone (for instance, the memory zone maintainedin the memory of 605 in FIG. 6) of the software encoder. In 807, it ischecked whether the frame currently being coded is an I frame. When notidentified as an I frame, motion estimation and motion compensation isperformed in 808. The flowchart in FIG. 10 shows details of this processperformed in 808. First of all, in 1001, motion estimation is performedbetween the images stored in frame memories A and B (just as written inthe final part of this paragraph, the decoded image of the prior frameis stored in frame memory B). The motion vector for each block is found,and this motion vector is sent to the output buffer. Next, in 1002,whether or not the current frame is a P+ frame is checked. When thecurrent frame is a P+ frame, the prediction image is synthesized in 1003utilizing positive rounding and this prediction image is stored in framememory C. On the other hand, when the current frame is a P− frame, theprediction image is synthesized in 1004 utilizing negative rounding andthis prediction image is stored in the frame memory C. Next, in 1005,the differential image between frame memories A and C is found andstored in frame memory A. Here, the process again returns to FIG. 8.Prior to starting the processing in 809, the input image is stored inframe memory A when the current frame is an I frame, and thedifferential image between the input image and the prediction image isstored in frame memory A when the current frame is a P frame (P+ or P−frame). In 809, DCT is applied to the image stored in frame memory A,and the DCT coefficients calculated here are sent to the output bufferafter being quantized. In 810, inverse quantization is performed to thequantized DCT coefficients and inverse DCT is applied. The imageobtained by applying inverse DCT is stored in frame memory B. Next in811, it is checked again whether the current frame is an I frame. Whenthe current frame is not an I frame, the images stored in frame memory Band C are added and the result is stored in frame memory B. The codingprocess of a frame ends here, and the image stored in frame memory Bbefore going into 813 is the reconstructed image of this frame (thisimage is identical with the one obtained at the decoding side). In 813,it is checked whether the frame whose coding has just finished is thefinal frame in the sequence. If this is true, the coding process ends.If this frame is not the final frame, 1 is added to N in 814, and theprocess again returns to 803 and the coding process for the next framestarts.

A software decoder 700 is shown in FIG. 7. After the coded bit stream701 is temporarily stored in the input buffer 702, this bit stream isthen loaded into the general-purpose processor 703. The program fordriving this general-purpose processor is loaded from a storage device708 which can be a hard disk, floppy disk, etc. and stored in a programmemory 704. This general-purpose processor also uses a process memory605 to perform the decoding. The decoded image obtained by the decodingprocess is temporarily stored in the output frame memory 706 and thensent out as the output image 707.

A flowchart of the decoding software for the software decoder 700 shownin FIG. 7 is shown in FIG. 11. The process starts in 1101, and it ischecked in 1102 whether input information is present. If there is noinput information, the decoding process ends in 1103. When inputinformation is present, distinction information of the prediction modeis input in 1104. The word “input” used here means that the informationstored in the input buffer (for instance 702 of FIG. 7) is loaded by thegeneral-purpose processor. In 1105, it is checked whether the encodingmode distinction information is “I”. When not “I”, the distinctioninformation for the rounding method is input and synthesis of theinterframe prediction image is performed in 1107. A flowchart showingdetails of the operation in 1107 is shown in FIG. 12. In 1201, a motionvector is input for each block. Then, in 1202, it is checked whether thedistinction information for the rounding method loaded in 1106 is a “+”.When this information is “+”, the frame currently being decoded is a P+frame. In this case, the prediction image is synthesized using positiverounding in 1203, and the prediction image is stored in frame memory D.Here, frame memory D signifies a portion of the memory zone of thesoftware decoder (for instance, this memory zone is obtained in theprocessing memory 705 in FIG. 7). When the distinction information ofthe rounding method is not “+”, the current frame being decoded is a P−frame. The prediction image is synthesized using negative rounding in1204 and this prediction image is stored in frame memory D. At thispoint, if a P+ frame is decoded as a P− frame due to some type of error,or conversely if a P− frame is decoded as a P+ frame, the correctprediction image is not synthesized in the decoder and the quality ofthe decoded image deteriorates. After synthesizing the prediction image,the operation returns to FIG. 11 and the quantized DCT coefficients isinput in 1108. Inverse quantization and inverse DCT is then applied tothese coefficients and the resulting image is stored in frame memory E.In 1109, it is checked again whether the frame currently being decodedis an I frame. If the current frame is not an I frame, images stored inframe memory D and E are added in 1110 and the resulting sum image isstored in frame memory E. The image stored in frame memory E beforestarting the process in 1111 is the reconstructed image. This imagestored in frame memory E is output to the output frame memory (forinstance, 706 in FIG. 7) in 1111, and then output from the decoder asthe reconstructed image. The decoding process for a frame is completedhere and the process for the next frame starts by returning to 1102.

When a software based on the flowchart shown in FIGS. 8-12 is run in thesoftware image encoders or decoders, the same effect as when customcircuits and custom chips are utilized are obtained.

A storage media (recording media) with the bit stream generated by thesoftware encoder 601 of FIG. 6 being recorded is shown in FIG. 13. It isassumed that the algorithms shown in the flowcharts of FIGS. 8-10 isused in the software encoder. Digital information is recordedconcentrically on a recording disk 1301 capable of recording digitalinformation (for instance magnetic disks, optical disk, etc.). A portion1302 of the information recorded on this digital disk includes:prediction mode distinction information 1303, 1305, 1308, 1311, and1314; rounding method distinction information 1306, 1309, 1312, and1315; and motion vector and DCT coefficient information 1304, 1307,1310, 1313, and 1316. Information representing ‘I’ is recorded in 1303,‘P’ is recorded in 1305, 1308, 1311, and 1314, ‘+’ is recorded in 1306,and 1312, and ‘−’ is recorded in 1309, and 1315. In this case, ‘I’ and‘+’ can be represented by a single bit of 0, and ‘P’ and ‘−’ can berepresented by a single bit of 1. Using this representation, the decodercan correctly interpret the recorded information and the correctreconstructed image is synthesized. By storing a coded bit stream in astorage media using the method described above, the accumulation ofrounding errors is prevented when the bit stream is read and decoded.

A storage media with the bit stream of the coded data of the imagesequence shown in FIG. 5 being recorded is shown in FIG. 15. Therecorded bit stream includes information related to P+, P−, and Bframes. In the same way as in 1301 of FIG. 13, digital information isrecorded concentrically on a record disk 1501 capable for recordingdigital information(for instance, magnetic disks, optical disks, etc.).A portion 1502 of the digital information recorded on this digital diskincludes: prediction mode distinction information 1503, 1505, 1508,1510, and 1513; rounding method distinction information 1506, and 1512;and motion vector and DCT coefficient information 1504, 1507, 1509,1511, and 1514. Information representing ‘I’ is recorded in 1503, ‘P’ isrecorded in 1505, and 1510, ‘B’ is recorded in 1508, and 1513, ‘+’ isrecorded in 1505, and ‘−’ is recorded in 1511. In this case, ‘I’, ‘P’and ‘B’ can be represented respectively by two bit values 00, 01, and10, and ‘+’ and ‘−’ can be represented respectively by one bit values 0and 1. Using this representation, the decoder can correctly interpretthe recorded information and the correct reconstructed is synthesized.In FIG. 15, information related to frame 501 (I frame) in FIG. 5 is 1503and 1504, information related to 502 (B frame) is 1508 and 1509,information related to frame 503 (P+ frame) is 1505 and 1507,information related to frame 504 (B frame) is 1513 and 1514, andinformation related to frame 505 (P− frame) is 1510 and 1512. Whencoding image sequences are coded using B frames, the transmission orderand display order of frames are usually different. This is because theprevious and subsequent reference images need to be coded before theprediction image for the B frame is synthesized. Consequently, in spiteof the fact that the frame 502 is displayed before frame 503,information related to frame 503 is transmitted before informationrelated to frame 502. As described above, there is no need to usemultiple rounding methods for B frames since motion compensation in Bframes do not cause accumulation of rounding errors. Therefore, as shownin this example, information that specifies rounding methods (e.g. ‘+’and ‘−’) is not transmitted for B frames. Thus for instance, even ifonly positive rounding is applied to B frames, the problem ofaccumulated rounding errors does not occur. By storing coded bit streamscontaining information related to B frames in a storage media in the waydescribed above, the occurrence of accumulated rounding errors can beprevented when this bit stream is read and decoded.

Specific examples of coders and decoders using the coding methoddescribed in this specification is shown in FIG. 14. The image codingand decoding method can be utilized by installing image coding anddecoding software into a computer 1401. This software is recorded insome kind of storage media (CD-ROM, floppy disk, hard disk, etc.) 1412,loaded into a computer and then used. Additionally, the computer can beused as an image communication terminal by connecting the computer to acommunication lines. It is also possible to install the decoding methoddescribed in this specification into a player device 1403 that reads anddecodes the coded bit stream recorded in a storage media 1402. In thiscase, the reconstructed image signal can be displayed on a televisionmonitor 1404. The device 1403 can be used only for reading the coded bitstream, and in this case, the decoding device can be installed in thetelevision monitor 1404. It is well known that digital data transmissioncan be realized using satellites and terrestrial waves. A decodingdevice can also be installed in a television receiver 1405 capable ofreceiving such digital transmissions. Also, a decoding device can alsobe installed inside a set top box 1409 connected to asatellite/terrestrial wave antenna, or a cable 1408 of a cabletelevision system, so that the reconstructed images can be displayed ona television monitor 1410. In this case, the decoding device can beincorporated in the television monitor rather than in the set top box,as in the case of 1404. The layout of a digital satellite broadcastsystem is shown in 1413, 1414 and 1415. The video information in thecoded bit stream is transmitted from a broadcast station 1413 to acommunication or broadcast satellite 1414. The satellite receives thisinformation, sends it to a home 1415 having equipment for receivingsatellite broadcast programs, and the video information is reconstructedand displayed in this home using devices such as a television receiveror a set top box. Digital image communication using mobile terminals1406 has recently attracted considerable attention, due to the fact thatimage communication at very low bit rates has become possible. Digitalportable terminals can be categorized in the following three types: atransceiver having both an encoder and decoder; a transmitter havingonly an encoder; and a receiver having only a decoder. An encodingdevice can be installed in a video camera recorder 1407. The camera canalso be used just for capturing the video signal and this signal can besupplied to a custom encoder 1411. All of the devices or systems shownin this drawing can be equipped with the coding or/and decoding methoddescribed in this specification. By using this coding or/and decodingmethod in these devices or systems, images of higher quality comparedwith those obtained using conventional technologies can be obtained.

The following variations are clearly included within the scope of thisinvention.

(i) A prerequisite of the above described principle was the use of blockmatching as a motion compensation method. However, this invention isfurther capable of being applied to all image sequence coding anddecoding methods in which motion compensation is performed by taking avalue for the vertical and horizontal components of the pixel motionvector that is other than an integer multiple of the sampling period inthe vertical and horizontal directions of the pixel, and then finding,by interpolation, the intensity value of a position where the samplevalue is not present. Thus, this invention is applicable, for example,to the global motion compensation described in Japanese PatentApplication No. 8-60572 published as Japanese Patent ApplicationLaid-Open No. 9-252470, and the warping prediction described in JapanesePatent Application No. 8-249601 published as Japanese Patent ApplicationLaid-Open No. 10-98729.

(ii) The description of the invention only mentioned the case where avalue integral multiple of ½ was taken for the horizontal and verticalcomponents of the motion vector. However, this invention is alsogenerally applicable to methods in which integral multiples of 1/d (d isa positive integer and also an even number) are allowed for thehorizontal and vertical components of the motion vector. However, when dbecomes large, the divisor for division in bilinear interpolation(square of d, see Equation 2) also becomes large, so that in contrast,the probability of results from normal division reaching a value of 0.5become low. Accordingly, when performing only positive rounding, theabsolute value of the expectation for rounding errors becomes small andthe bad effects caused by accumulated errors become less conspicuous.Also applicable to the method of this invention, is a motioncompensation method where for instance, the d value is variable, bothpositive rounding and negative rounding are used when d is smaller thana fixed value, and only positive rounding or only negative rounding isused when the value of d is larger than a fixed value.

(iii) As mentioned in the prior art, when DCT is utilized as an errorcoding method, the adverse effects from accumulated rounding errors areprone to appear when the quantized step size of the DCT coefficient islarge. However a method is also applicable to the invention, in which,when the quantization step size of DCT coefficients is larger than athreshold value then both positive rounding and negative rounding areused. When the quantization step size of the DCT coefficients is smallerthan the threshold value then only positive rounding or only negativerounding is used.

(iv) In cases where error accumulations occur on the luminance plane andcases where error accumulations occur on the chrominance plane, the badeffects on the reconstructed images are generally more serious in thecase of error accumulations on the chrominance plane. This is due to thefact that rather than cases where the image darkens or lightensslightly, cases where overall changes in the image color happen are moreconspicuous. However, a method is also applicable to this invention inwhich both positive rounding and negative rounding are used for thechrominance signal, and only positive rounding or negative rounding isused for the luminance signal.

As described in the description of related art, ¼ pixel accuracy motionvectors obtained by halving the ½ pixel accuracy motion vectors arerounded to ½ pixel accuracy in H.263. However by adding certain changesto this method, the absolute expectation value for rounding errors canbe reduced. In H.263 that was mentioned in the prior art, a value whichis half the horizontal or vertical components of the motion vector forthe luminance plane is expressed as r+s/4 (r is an integer, s is aninteger less than 4 and not smaller than 0), and when s is 1 or 3, arounding operation is performed to obtain a 2. This operation can bechanged as follows: When s is 1, a rounding operation is performed toobtain a 0, and when s is 3 a 1 is be added to r to make s a 0. Byperforming these operations, the number of times that the intensityvalues at positions 406-408 in FIG. 4 is definitely reduced (Probabilitythat horizontal and vertical components of motion vector will be aninteger become high.) so that the absolute expectation value for therounding error becomes small. However, even if the size of the erroroccurring in this method can be limited, the accumulation of errorscannot be completely prevented.

(v) The invention described in this application is applicable to amethod that obtains the final interframe prediction image by averagingthe prediction images obtained by different motion compensation methods.For example, in the method described in Japanese Patent Application No.8-3616 published as Japanese Patent Application Laid-Open No. 9-200763,interframe prediction images obtained by the following two methods areaveraged: block matching in which a motion vector is assigned to each16×16 pixel block; and block matching in which a motion vector isassigned to each 8×8 pixel block. In this method, rounding is alsoperformed when calculating the average of the two prediction images.When only positive rounding is continuously performed in this averagingoperation, a new type of rounding error accumulates. This problem can besolved by using multiple rounding methods for this averaging operation.In this method, negative rounding is performed in the averagingoperation when positive rounding is performed in block matching.Conversely, positive rounding is performed in the averaging operationwhen negative rounding is performed in block matching. By usingdifferent rounding methods for the averaging operation and blockmatching, the rounding errors from two different sources are cancelledwithin the same frame.

(vi) When utilizing a method that alternately locates P+ frames and P−frames along the time axis, the encoder or the decoder needs todetermine whether the currently processed P frame is a P+ frame or a P−frame. The following is an example of such identification method: Acounter counts the number of P frames after the most recently coded ordecoded I frame, and the current P frame is a P+ frame when the numberis odd, and a P− frame when the number is even (this method is referredto as an implicit scheme). There is also a method for instance, thatwrites into the header section of the coded image information,information to identify whether the currently coded P frame at theencoder is a P+ frame or a P− frame (this method is referred to as anexplicit scheme). Compared with the implicit method, this method is wellable to withstand transmission errors, since there is no need to countthe number of P frames.

Additionally, the explicit method has the following advantages: Asdescribed in “Description for Related Art”, past encoding standards(such as MPEG-1 or MPEG-2) use only positive rounding for motioncompensation. This means for instance that the motion estimation/motioncompensation devices (for example equivalent to 106 in FIG. 1) forMPEG-1/MPEG-2 on the market are not compatible with coding methods thatuses both P+ frames and P− frames. It is assumed that there is a decoderwhich can decode bit streams generated by a coding method that uses P+frames and P− frames. In this case if the decoder is based on the abovementioned implicit method, then it will be difficult to develop anencoder that generates bit streams that can be correctly decoded by theabove mentioned decoder, using the above mentioned motionestimation/compensation device for MPEG-1/MPEG-2. However, if thedecoder is based on the above mentioned explicit method, this problemcan be solved. An encoder using an MPEG-1/MPEG-2 motionestimation/motion compensation device can continuously send P+ frames,by continuously writing rounding method distinction informationindicating positive rounding into the frame information header. Whenthis is performed, a decoder based on the explicit method can correctlydecode the bit stream generated by this encoder. Of course, it should bemore likely in such case that the accumulation of rounding errorsoccurs, since only P+ frames are present. However, error accumulation isnot a serious problem in cases where the encoder uses only small valuesas the quantization step size for the DCT coefficients (an example forsuch coders is a custom encoder used only for high rate coding). Inaddition to this interoperability between past standards, the explicitmethod further have the following advantages:(a) the equipment cost forhigh rate custom encoders and coders not prone to rounding erroraccumulation due to frequent insertion of I frames can be reduced byinstalling only positive or negative rounding as the pixel valuerounding method for motion compensation; and(b) the above encoders notprone to rounding error accumulation have the advantage in that there isno need to decide whether to code the current frame as a P+ or P− frame,and the processing is simplified.

(vii) The invention described in this specification is applicable tocoding and decoding methods that applies filtering accompanying roundingto the interframe prediction images. For instance, in the internationalstandard H.261 for image sequence coding, a low-pass filter (called aloop filter) is applied to block signals whose motion vectors are not 0in interframe prediction images. Also, in H.263, filters can be used tosmooth out discontinuities on block boundaries (blocking artifacts). Allof these filters perform weighted averaging to pixel intensity valuesand rounding is then performed on the averaged intensity values. Evenfor these cases, selective use of positive rounding and negativerounding is effective for preventing error accumulation.

(viii) Besides I P+ P− P+ P− . . . , various methods for mixing P+frames and P− frames such as I P+ P+ P− P− P+ P+or I P+ P− P− P+ P+ . .. are applicable to the method of this invention. For instance, using arandom number generator that outputs 0 and 1 both at a probability of 50percent, the encoder can code a P+ and P− frame when the output is 0 and1, respectively. In any case, the less the difference in probabilitythat P+ frames and P− frames occur in a certain period of time, the lessthe rounding error accumulation is prone to occur. Further, when theencoder is allowed to mix P+ frames and P− frames by an arbitrarymethod, the encoder and decoder must operate based on the explicitmethod and not with the implicit method described above. Accordingly,the explicit method is superior when viewed from the perspective ofallowing flexibility configuration for the encoder and decoder.

(ix) The invention described in this specification does not limit thepixel value interpolation method to bilinear interpolation.Interpolation methods for intensity values can generally be described bythe following equation: $\begin{matrix}\text{[Equation 5]} & \quad \\{{R\left( {{x + r},{y + s}} \right)} = {T\left( {\sum\limits_{j = {- \infty}}^{\infty}{\sum\limits_{j = {- \infty}}^{\infty}{{h\left( {{r - j},{s - k}} \right)}{R\left( {{x + j},{y + k}} \right)}}}} \right)}} & (5)\end{matrix}$

where, r and s are real numbers, h(r, s) is a function for interpolatingthe real numbers, and T(z) is a function for rounding the real number z.The definitions of R (x, y), x, and y are the same as in Equation 4.Motion compensation utilizing positive rounding is performed when T (z)is a function representing positive rounding, and motion compensationutilizing negative rounding is performed when the function representingnegative rounding. This invention is applicable to interpolation methodsthat can be described using Equation 5. For instance, bilinearinterpolation can be described by defining h(r, s) as shown below.$\begin{matrix}\text{[Equation 6]} & \quad \\\begin{matrix}{{{h\left( {r,s} \right)} = {\left( {1 - {r}} \right)\quad \left( {1 - {s}} \right)}},} & {{0 \leq {r} \leq 1},{0 \leq {s} \leq 1},} \\{0,} & {{otherwise}.}\end{matrix} & (6)\end{matrix}$

However, if for instance h(r,s) is defined as shown below,$\begin{matrix}\text{[Equation 7]} & \quad \\\begin{matrix}{{{h\left( {r,s} \right)} = {1 - {r} - {s}}},} & {{0 \leq {{r} + {s}} \leq 1},{{rs} < 0},} \\{\quad {{1 - {r}},}} & {{{r} \geq {s}},{{r} \leq 1},{{rs} \geq 0},} \\{\quad {{1 - {s}},}} & {{{s} > {r}},{{s} \leq 1},{{rs} > 0},} \\{\quad {0,}} & {{otherwise}.}\end{matrix} & (7)\end{matrix}$

then an interpolation method different from bilinear interpolation isimplemented but the invention is still applicable.

(x) The invention described in this specification does not limit thecoding method for error images to DCT (discrete cosine transform). Forinstance, wavelet transform (for example, M. Antonioni, et. al, “ImageCoding Using Wavelet Transform” IEEE Trans. Image Processing, vol. 1,no.2, April 1992) and Walsh-Hadamard transform (for example, A. N.Netravalli and B. G. Haskell, “Digital Pictures”, Plenum Press, 1998)are also applicable to this invention.

What is claimed is:
 1. An image decoder comprising: a demultiplexerwhich extracts motion vector information and quantized DCT coefficientsfrom input information to be decoded; a dequantizer which dequantizesthe quantized DOT coefficients to obtain DOT coefficients; an inverseDOT converter which performs inverse DOT conversion on the DOTcoefficients to obtain an error image; a prediction image synthesizerwhich synthesizes a prediction image by performing motion compensationusing the motion vector information and a reference image which is apreviously decoded image; and an adder which adds the prediction imageto the error image to obtain a decoded image; wherein the motioncompensation includes specifying either a positive rounding method or anegative rounding method for interpolating intensity values of pixels inperforming the motion compensation.
 2. An image decoder comprising: ademultiplexer which extracts motion vector information and quantized DCTcoefficients from input information to be decoded; a prediction imagesynthesizer which synthesizes a prediction image by performing motioncompensation using the motion vector information and a reference imagewhich is a previously decoded image; and an adder which synthesizes adecoded image by adding the prediction image to an error image obtainedby applying dequantization and inverse DCT conversion to the quantizedDCT coefficients; wherein the motion compensation is performed withhalf-pixel accuracy and uses bilinear interpolation to calculateintensity values of chrominance or luminance at points where no pixelsactually exist in the reference image, the bilinear interpolation beingperformable using a positive rounding method and a negative roundingmethod; and wherein the bilinear interpolation is performed using apositive rounding method in accordance with the following equations:Ib=[(La+Lb+1)/2], Ic=[(La+Lc+1)/2], and Id=[(La+Lb+Lc+Ld+2)/4], and isperformed using a negative rounding method in accordance with thefollowing equations: Ib=[(La+Lb)/2], Ic=[(La+Lc)/2], andId=[(La+Lb+Lc+Ld+1)/4], where La is an intensity value of a first pixelin the reference image, Lb is an intensity value of a second pixel inthe reference image which is horizontally adjacent to the first pixel,Lc is an intensity value of a third pixel in the reference image whichis vertically adjacent to the first pixel, and Ld is an intensity valueof a fourth pixel in the reference image which is vertically adjacent tothe second pixel and horizontally adjacent to the third pixel, Ib is aninterpolated intensity value at a midpoint between a position of thefirst pixel and a position of the second pixel, Ic is an interpolatedintensity value at a midpoint between the position of the first pixeland a position of the third pixel, and Id is an interpolated intensityvalue of a midpoint between the position of the first pixel, theposition of the second pixel, the position of the third pixel, and aposition of the fourth pixel.